IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v21y2024i12p1648-d1540703.html
   My bibliography  Save this article

Variations in Cycling Distances by Trip Purpose and Socio-Demographic Attributes: Implications for Spatial Scales to Assess Environmental Correlates of Cycling

Author

Listed:
  • Firas Mohamed

    (Centre for Urban Transitions, Swinburne University of Technology, Melbourne 3122, Australia
    Department of Mathematical Sciences, South Eastern University of Sri Lanka, Sammanthurai 32200, Sri Lanka)

  • Manoj Chandrabose

    (Centre for Urban Transitions, Swinburne University of Technology, Melbourne 3122, Australia
    Baker Heart and Diabetes Institute, Melbourne 3004, Australia)

  • Abdur Rahim Mohammad Forkan

    (School of Science, Computing and Engineering Technology, Swinburne University of Technology, Melbourne 3122, Australia)

  • Neville Owen

    (Centre for Urban Transitions, Swinburne University of Technology, Melbourne 3122, Australia
    Baker Heart and Diabetes Institute, Melbourne 3004, Australia)

  • Takemi Sugiyama

    (Centre for Urban Transitions, Swinburne University of Technology, Melbourne 3122, Australia
    Baker Heart and Diabetes Institute, Melbourne 3004, Australia)

Abstract

To better understand environmental attributes associated with cycling, it is necessary to identify an area within which such attributes are measured. Various sizes of a “buffer” drawn from home have been used for this purpose. The distances adults cycle to/from their homes may inform the determination of empirically supported buffer sizes. We examined the distribution of cycling distances using Australian travel survey data collected between 2012 and 2020. We used a Random Forest model to identify the relative importance of factors influencing participant’s cycling distance and then reported variations in cycling distances by the most important factors. Of the 73,142 survey participants who were aged between 20 and 74 and reported at least one trip on the survey day, 1676 (67% men) reported 3446 home-based cycling trips, with a median distance of 3.5 km. The most important factor was trip purpose, followed by gender. The median distances were 1.8 km for utilitarian, 5.3 km for commuting and 3.7 km for recreational cycling trips. Men cycled longer distances than women, particularly for commuting and recreational cycling. The significant variation in cycling distance by trip purpose implies the need for having purpose-specific spatial scales in identifying environmental attributes associated with cycling more accurately.

Suggested Citation

  • Firas Mohamed & Manoj Chandrabose & Abdur Rahim Mohammad Forkan & Neville Owen & Takemi Sugiyama, 2024. "Variations in Cycling Distances by Trip Purpose and Socio-Demographic Attributes: Implications for Spatial Scales to Assess Environmental Correlates of Cycling," IJERPH, MDPI, vol. 21(12), pages 1-11, December.
    • Handle: RePEc:gam:jijerp:v:21:y:2024:i:12:p:1648-:d:1540703
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/21/12/1648/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/21/12/1648/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wright, Marvin N. & Ziegler, Andreas, 2017. "ranger: A Fast Implementation of Random Forests for High Dimensional Data in C++ and R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 77(i01).
    2. Wei, Pengfei & Lu, Zhenzhou & Song, Jingwen, 2015. "Variable importance analysis: A comprehensive review," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 399-432.
    3. Mohammad Javad Koohsari & Rachel Cole & Koichiro Oka & Ai Shibata & Akitomo Yasunaga & Tomoya Hanibuchi & Neville Owen & Takemi Sugiyama, 2020. "Associations of built environment attributes with bicycle use for transport," Environment and Planning B, , vol. 47(9), pages 1745-1757, November.
    4. Suzanne Mavoa & Nasser Bagheri & Mohammad Javad Koohsari & Andrew T. Kaczynski & Karen E. Lamb & Koichiro Oka & David O’Sullivan & Karen Witten, 2019. "How Do Neighbourhood Definitions Influence the Associations between Built Environment and Physical Activity?," IJERPH, MDPI, vol. 16(9), pages 1-16, April.
    5. Liang Ma & Jennifer Dill & Cynthia Mohr, 2014. "The objective versus the perceived environment: what matters for bicycling?," Transportation, Springer, vol. 41(6), pages 1135-1152, November.
    6. Gössling, Stefan & Choi, Andy & Dekker, Kaely & Metzler, Daniel, 2019. "The Social Cost of Automobility, Cycling and Walking in the European Union," Ecological Economics, Elsevier, vol. 158(C), pages 65-74.
    7. Solveig Nordengen & Denise Christina Ruther & Amund Riiser & Lars Bo Andersen & Ane Solbraa, 2019. "Correlates of Commuter Cycling in Three Norwegian Counties," IJERPH, MDPI, vol. 16(22), pages 1-18, November.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Backer, David & Billing, Trey, 2024. "Forecasting the prevalence of child acute malnutrition using environmental and conflict conditions as leading indicators," World Development, Elsevier, vol. 176(C).
    2. Mariana Oliveira & Luís Torgo & Vítor Santos Costa, 2021. "Evaluation Procedures for Forecasting with Spatiotemporal Data," Mathematics, MDPI, vol. 9(6), pages 1-27, March.
    3. Asma Shaheen & Javed Iqbal, 2018. "Spatial Distribution and Mobility Assessment of Carcinogenic Heavy Metals in Soil Profiles Using Geostatistics and Random Forest, Boruta Algorithm," Sustainability, MDPI, vol. 10(3), pages 1-20, March.
    4. Rosa Arroyo & Lidón Mars & Tomás Ruiz, 2018. "Perceptions of Pedestrian and Cyclist Environments, Travel Behaviors, and Social Networks," Sustainability, MDPI, vol. 10(9), pages 1-21, September.
    5. Verma, Meghna & Rahul, T.M. & Reddy, Peesari Vamshidhar & Verma, Ashish, 2016. "The factors influencing bicycling in the Bangalore city," Transportation Research Part A: Policy and Practice, Elsevier, vol. 89(C), pages 29-40.
    6. Bokelmann, Björn & Lessmann, Stefan, 2024. "Improving uplift model evaluation on randomized controlled trial data," European Journal of Operational Research, Elsevier, vol. 313(2), pages 691-707.
    7. Joel Podgorski & Oliver Kracht & Luis Araguas-Araguas & Stefan Terzer-Wassmuth & Jodie Miller & Ralf Straub & Rolf Kipfer & Michael Berg, 2024. "Groundwater vulnerability to pollution in Africa’s Sahel region," Nature Sustainability, Nature, vol. 7(5), pages 558-567, May.
    8. Shang, Xiaobing & Su, Li & Fang, Hai & Zeng, Bowen & Zhang, Zhi, 2023. "An efficient multi-fidelity Kriging surrogate model-based method for global sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    9. Matteo Rucco & Giovanna Viticchi & Lorenzo Falsetti, 2020. "Towards Personalized Diagnosis of Glioblastoma in Fluid-Attenuated Inversion Recovery (FLAIR) by Topological Interpretable Machine Learning," Mathematics, MDPI, vol. 8(5), pages 1-27, May.
    10. Chakravorty, Bhaskar & Arulampalam, Wiji & Bhatiya, Apurav Yash & Imbert, Clément & Rathelot, Roland, 2024. "Can information about jobs improve the effectiveness of vocational training? Experimental evidence from India," Journal of Development Economics, Elsevier, vol. 169(C).
    11. Arjan S. Gosal & Janine A. McMahon & Katharine M. Bowgen & Catherine H. Hoppe & Guy Ziv, 2021. "Identifying and Mapping Groups of Protected Area Visitors by Environmental Awareness," Land, MDPI, vol. 10(6), pages 1-14, May.
    12. Albert Stuart Reece & Gary Kenneth Hulse, 2022. "European Epidemiological Patterns of Cannabis- and Substance-Related Congenital Neurological Anomalies: Geospatiotemporal and Causal Inferential Study," IJERPH, MDPI, vol. 20(1), pages 1-35, December.
    13. Foutzopoulos, Giorgos & Pandis, Nikolaos & Tsagris, Michail, 2024. "Predicting full retirement attainment of NBA players," MPRA Paper 121540, University Library of Munich, Germany.
    14. Michael Parzinger & Lucia Hanfstaengl & Ferdinand Sigg & Uli Spindler & Ulrich Wellisch & Markus Wirnsberger, 2020. "Residual Analysis of Predictive Modelling Data for Automated Fault Detection in Building’s Heating, Ventilation and Air Conditioning Systems," Sustainability, MDPI, vol. 12(17), pages 1-18, August.
    15. Yun, Wanying & Lu, Zhenzhou & Feng, Kaixuan & Li, Luyi, 2019. "An elaborate algorithm for analyzing the Borgonovo moment-independent sensitivity by replacing the probability density function estimation with the probability estimation," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 99-108.
    16. Dugan, Anna & Mayer, Jakob & Thaller, Annina & Bachner, Gabriel & Steininger, Karl W., 2022. "Developing policy packages for low-carbon passenger transport: A mixed methods analysis of trade-offs and synergies," Ecological Economics, Elsevier, vol. 193(C).
    17. Mohamed Zine & Fouzi Harrou & Mohammed Terbeche & Mohammed Bellahcene & Abdelkader Dairi & Ying Sun, 2023. "E-Learning Readiness Assessment Using Machine Learning Methods," Sustainability, MDPI, vol. 15(11), pages 1-22, June.
    18. Mário Meireles & Paulo J. G. Ribeiro, 2020. "Digital Platform/Mobile App to Boost Cycling for the Promotion of Sustainable Mobility in Mid-Sized Starter Cycling Cities," Sustainability, MDPI, vol. 12(5), pages 1-27, March.
    19. Adeline Gu'eret & Wolf-Peter Schill & Carlos Gaete-Morales, 2024. "Impacts of electric carsharing on a power sector with variable renewables," Papers 2402.19380, arXiv.org, revised Oct 2024.
    20. Masayoshi Mase & Art B. Owen & Benjamin B. Seiler, 2021. "Cohort Shapley value for algorithmic fairness," Papers 2105.07168, arXiv.org.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:21:y:2024:i:12:p:1648-:d:1540703. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.